mlsanityData to 14 Oct 2026

Channel-Aware Distillation Transformer for Depth Estimation on Nano Drones

arXiv 2303.10386 ↗First posted 18 Mar 2023cs.RO cs.CVcited by 1

Not on the map. Why?

Abstract (arXiv)

Autonomous navigation of drones using computer vision has achieved promising performance. Nano-sized drones based on edge computing platforms are lightweight, flexible, and cheap, thus suitable for exploring narrow spaces. However, due to their extremely limited computing power and storage, vision algorithms designed for high-performance GPU platforms cannot be used for nano drones. To address this issue this paper presents a lightweight CNN depth estimation network deployed on nano drones for obstacle avoidance. Inspired by Knowledge Distillation (KD), a Channel-Aware Distillation Transformer (CADiT) is proposed to facilitate the small network to learn knowledge from a larger network. The proposed method is validated on the KITTI dataset and tested on a nano drone Crazyflie, with an ultra-low power microprocessor GAP8.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 29 of its 56 references that are in the map. First posted on arXiv 18 Mar 2023.

Builds on

29 of 56 references.

References · 29

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2015Distilling the Knowledge in a Neural Networkcited by 10,324
  3. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,845
  4. 2014FitNets: Hints for Thin Deep Netscited by 1,653
  5. 2014Depth Map Prediction from a Single Image using a Multi-Scale Deep Networkcited by 1,274
  6. 2016Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfercited by 1,077
  7. 2017Deep Mutual Learningcited by 628
  8. 2014Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecturecited by 483
  9. 2019On the Efficacy of Knowledge Distillationcited by 381
  10. 2018GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Posecited by 342
  11. 2020D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometrycited by 206
  12. 2021Does Knowledge Distillation Really Work?cited by 190
17 more
  1. 2020On the uncertainty of self-supervised monocular depth estimationcited by 182
  2. 2020Channel-wise Knowledge Distillation for Dense Predictioncited by 163
  3. 2020HR-Depth: High Resolution Self-Supervised Monocular Depth Estimationcited by 115
  4. 2022Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimationcited by 100
  5. 2019FastDepth: Fast Monocular Depth Estimation on Embedded Systemscited by 94
  6. 2022Knowledge Distillation via the Target-aware Transformercited by 70
  7. 2021Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimationcited by 63
  8. 2021Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth Estimationcited by 55
  9. 2019Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimationcited by 49
  10. 2017Learning to Fly by Crashingcited by 41
  11. 2022Deep Digging into the Generalization of Self-Supervised Monocular Depth Estimationcited by 24
  12. 2018A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Dronescited by 23
  13. 2020Channel Distillation: Channel-Wise Attention for Knowledge Distillationcited by 21
  14. 2021Boosting Light-Weight Depth Estimation Via Knowledge Distillationcited by 16
  15. 2021Sniffy Bug: A Fully Autonomous Swarm of Gas-Seeking Nano Quadcopters in Cluttered Environmentscited by 13
  16. 2016Efficient Optical flow and Stereo Vision for Velocity Estimation and Obstacle Avoidance on an Autonomous Pocket Dronecited by 11
  17. 2022NanoFlowNet: Real-time Dense Optical Flow on a Nano Quadcoptercited by 10

Built on by

Cited by year

Citing papers per year: 2024: 1.

1 paper.

  1. 2024Predicting High-precision Depth on Low-Precision Devices Using 2D Hilbert Curvescited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Autonomous Navigation at the Nano-Scale: Algorithms, Architectures, and Constraints ↗
  2. 2026BlankSkip: Early-exit Object Detection onboard Nano-drones
  3. 2023Ultra-low Power Deep Learning-based Monocular Relative Localization Onboard Nano-quadrotors
  4. 2025CoDrone: Autonomous Drone Navigation Assisted by Edge and Cloud Foundation Models
  5. 2026CSCWD: Cross-Scale Channel-wise Knowledge Distillation for Lightweight Tiny Object Detection on Edge Devices
  6. 2024A Heterogeneous RISC-V based SoC for Secure Nano-UAV Navigation
  7. 2025A Performance Analysis of You Only Look Once Models for Deployment on Constrained Computational Edge Devices in Drone Applications
  8. 2025Self-Supervised Learning to Fly using Efficient Semantic Segmentation and Metric Depth Estimation for Low-Cost Autonomous UAVs